7 papers · 1 filter
Interpreting Quantum Learning Models via Stochastic Processes
Johannes Fankhauser, Lukas J. Fiderer, Hans J. Briegel
Quantum machine learning models define probabilistic input--output maps through coherent quantum evolution and measurement. While such models can exhibit computational advantages,…
General expressions for the quantum Fisher information matrix with applications to discrete quantum imaging
Lukas J. Fiderer, Tommaso Tufarelli, Samanta Piano +1
The quantum Fisher information matrix is a central object in multiparameter quantum estimation theory. It is usually challenging to obtain analytical expressions for it because mos…
Neural-Network Heuristics for Adaptive Bayesian Quantum Estimation
Lukas J. Fiderer, Jonas Schuff, Daniel Braun
Quantum metrology promises unprecedented measurement precision but suffers in practice from the limited availability of resources such as the number of probes, their coherence time…
Improving the dynamics of quantum sensors with reinforcement learning
Jonas Schuff, Lukas J. Fiderer, Daniel Braun
Recently proposed quantum-chaotic sensors achieve quantum enhancements in measurement precision by applying nonlinear control pulses to the dynamics of the quantum sensor while usi…
Maximal Quantum Fisher Information for Mixed States
Lukas J. Fiderer, Julien M. E. Fraïsse, Daniel Braun
We study quantum metrology for unitary dynamics. Analytic solutions are given for both the optimal unitary state preparation starting from an arbitrary mixed state and the correspo…
A quantum-chaotic cesium-vapor magnetometer
Lukas J. Fiderer, Daniel Braun
Quantum-enhanced measurements represent the path towards the best measurement precision allowed by the laws of quantum mechanics. Known protocols usually rely on the preparation of…